doi:10.1136/bmjopen-2025-106685engArtés, CarmenPorras-Segovia, AlejandroRuiz-Veguilla, MiguelGiner, LucasGarcia-Campayo, JavierLópez del Hoyo, YolandaAlejandra-Saiz, PilarGarcía-Fernández, AinoaMartínez-Jambrina, Juan JoséVilla-Díez, RocíoGili, MargalidaRoca, Miquelde Andrés, FernandoPérez Sola, VíctorElices, Matilde E.Grande, IriaCebria, Ana IsabelIrigoyen-Otiñano, MariaGalván-Santiago, LeonardoAguilar Garcia-Iturrospe, Eduardo JesúsMesones-Peral, JesúsMora-Marín, RafaelSierra, PîlarPenas-Lledo, EvaLLerena, AdrianLopez-Castroman, JorgeCruz, RaquelArrojo, ManuelOvejero, Santiagode la Torre-Luque, AlejandroPalao-Tarrero, ÁngelaVaquero-Lorenzo, ConcepciónToma, ClaudioBarrigon, Maria LuisaArtes, AntonioDíaz-Marsá, MarinaAyad-Ahmed, WalaIbáñez, ÁngelaDíaz-Sastre, CarmenSalvador-Robert, MercèÁlvarez-García, RaquelMata-Iturralde, LauraBenavente-López, SergioMuñoz-Lorenzo, LauraDi Stasio, Ezequiel FernandoCarmona-Camacho, RodrigoPeñuelas-Calvo, InmaculadaValencia, MiguelLópez Peña, PurificaciónAlbarracín-García, LucíaBaca-Garcia, EnriqueDesigning interventions guided by digital phenotype and pharmacogenetics in Spain for suicidal behaviour based on retrospective data: the multicentre SMARTomicS study protocolART-2026-149531Introduction: Each year, suicide claims approximately 700 000 lives worldwide and generates a significant financial burden. Integrating genomic data, exposomic factors and digital phenotypes can enhance the development of short-term predictive models. Current knowledge and available tools provide the basis for designing personalised treatment strategies that incorporate real-time interventions to prevent suicide attempt recurrence cost-effectively. This study aims to develop a predictive algorithm for suicidal behaviour integrating psychiatric assessments, genetic risk markers, digital phenotypes and exposomic data. Methods and analysis: This protocol describes a retrospective multicentre study that will recruit participants with a clinical history of suicide across 25 hospitals across Spain with a catchment area of 8.6 million people (17.8% of Spain’s population). Our sample target is over 5000 participants, aged over 12 years old, ensuring 93.5% statistical power for genetic analysis. Eligible participants must be over 12 years old. Data collection will include psychiatric assessments, biospecimen collections (DNA, RNA, plasma and serum), Google Takeout data for digital phenotyping, and a standardised set of administrative and clinical data registered for each patient. Genotyping will be performed with the Axiom Spanish array (>750 000 markers), and genome-wide association studies (GWAS) will be performed after genetic imputation in a whole sample of >10 000 individuals (5000 suicide attempters; 5000 controls). Prescription and clinical history will also be retrospectively integrated, and codified data statistics forms will periodically be sent to the Government. Statistical analyses will combine traditional regression models and AI-based algorithms to identify predictive behavioural, genomic profiles, and digital markers of suicidal behaviour. Cost-effectiveness analyses of pharmacogenomic markers for antidepressant response will also be conducted. By successfully implementing this project, we aim to help reduce suicide reattempts and lessen the emotional and economic burden on families and the healthcare system.2026http://zaguan.unizar.es/record/17178410.1136/bmjopen-2025-106685http://zaguan.unizar.es/record/171784oai:zaguan.unizar.es:171784info:eu-repo/grantAgreement/ES/ISCIII/PI23-00614info:eu-repo/grantAgreement/ES/ISCIII/PMP24-00026BMJ Open 16 (2026), e106685 [10 pp.]by-nchttps://creativecommons.org/licenses/by-nc/4.0/deed.esinfo:eu-repo/semantics/openAccess